OpenRaiser/Intern-Atlas huggingface dataset:
Quality of Consumption: The Friendlier Side of Quality of Service
Venue: arXiv cs.CY 2015
Year: 2015

Cloud services today are increasingly built using functionality from other running services. In this paper, we question whether legacy Quality of Services (QoS) metrics and enforcement techniques are sufficient as they are producer centric. We argue that, similar to customer rating systems found in banking systems and many sharing economy apps (e.g., Uber and Airbnb), Quality of Consumption (QoC) should be introduced to capture different metrics about service consumers. We show how the combination of QoS and QoC, dubbed QoX, can be used by consumers and providers to improve the security and management of their infrastructure. In addition, we demonstrate how sharing information among other consumers and providers increase the value of QoX. To address the main challenge with sharing information, namely sybil attacks and mis-information, we describe how we can leverage cloud providers as vouching authorities to ensure the integrity of information. We present initial results in prototyping the appropriate abstractions and interfaces in a cloud environment, focusing on the design impact on both service providers and consumers.
Semantic issues in model-driven management of information system interoperability
Venue: arXiv cs.SE 2015
Year: 2015

The MISE Project (Mediation Information System Engineering) aims at providing collaborating organizations with a Mediation Information System (MIS) in charge of supporting interoperability of a collaborative network. MISE proposes an overall MIS design method according to a model-driven approach, based on model transformations. This MIS is in charge of managing (i) information, (ii) functions and (iii) processes among the information systems (IS) of partner organizations involved in the network. Semantic issues are accompanying this triple objective: How to deal with information reconciliation? How to ensure the matching between business functions and technical services? How to identify workflows among business processes? This article aims first, at presenting the MISE approach, second at defining the semantic gaps along the MISE approach and third at describing some past, current and future research works that deal with these issues. Finally and as a conclusion, the very "design-oriented" previous considerations are confronted with "run-time" requirements.
Enhanced Bilingual Evaluation Understudy
Venue: arXiv cs.CL 2015
Year: 2015

Our research extends the Bilingual Evaluation Understudy (BLEU) evaluation technique for statistical machine translation to make it more adjustable and robust. We intend to adapt it to resemble human evaluation more. We perform experiments to evaluate the performance of our technique against the primary existing evaluation methods. We describe and show the improvements it makes over existing methods as well as correlation to them. When human translators translate a text, they often use synonyms, different word orders or style, and other similar variations. We propose an SMT evaluation technique that enhances the BLEU metric to consider variations such as those.
A Sentence Meaning Based Alignment Method for Parallel Text Corpora Preparation
Venue: arXiv cs.CL 2015
Year: 2015

Text alignment is crucial to the accuracy of Machine Translation (MT) systems, some NLP tools or any other text processing tasks requiring bilingual data. This research proposes a language independent sentence alignment approach based on Polish (not position-sensitive language) to English experiments. This alignment approach was developed on the TED Talks corpus, but can be used for any text domain or language pair. The proposed approach implements various heuristics for sentence recognition. Some of them value synonyms and semantic text structure analysis as a part of additional information. Minimization of data loss was ensured. The solution is compared to other sentence alignment implementations. Also an improvement in MT system score with text processed with described tool is shown.
Fault Tolerance in Distributed Neural Computing
Venue: arXiv cs.NE 2015
Year: 2015

With the increasing complexity of computing systems, complete hardware reliability can no longer be guaranteed. We need, however, to ensure overall system reliability. One of the most important features of artificial neural networks is their intrinsic fault-tolerance. The aim of this work is to investigate whether such networks have features that can be applied to wider computational systems. This paper presents an analysis, in both the learning and operational phases, of a distributed feed-forward neural network with decentralised event-driven time management, which is insensitive to intermittent faults caused by unreliable communication or faulty hardware components. The learning rules used in the model are local in space and time, which allows efficient scalable distributed implementation. We investigate the overhead caused by injected faults and analyse the sensitivity to limited failures in the computational hardware in different areas of the network.
In-Field Logic Repair of Deep Sub-Micron CMOS Processors
Venue: arXiv cs.AR 2015
Year: 2015

Ultra Deep-Sub-Micron CMOS chips have to function correctly and reliably, not only during their early post-fabrication life, but also for their entire life span. In this paper, we present an architectural-level in-field repair technique. The key idea is to trade area for reliability by adding repair features to the system while keeping the power and the performance overheads as low as possible. In the case of permanent faults, spare blocks will replace the faulty blocks on the fly. Meanwhile by shutting down the main logic blocks, partial threshold voltage recovery can be achieved which will alleviate the ageing-related delays and timing issues. The technique can avoid fatal shut-downs in the system and will decrease the down-time, hence the availability of such a system will be preserved. We have implemented the proposed idea on a pipelined processor core using a conventional ASIC design flow. The simulation results show that by tolerating about 70% area overhead and less than 18% power overhead we can dramatically increase the reliability and decrease the downtime of the processor.
Fast Convergence in the Double Oral Auction
Venue: arXiv cs.GT 2015
Year: 2015

A classical trading experiment consists of a set of unit demand buyers and unit supply sellers with identical items. Each agent's value or opportunity cost for the item is their private information and preferences are quasi-linear. Trade between agents employs a double oral auction (DOA) in which both buyers and sellers call out bids or offers which an auctioneer recognizes. Transactions resulting from accepted bids and offers are recorded. This continues until there are no more acceptable bids or offers. Remarkably, the experiment consistently terminates in a Walrasian price. The main result of this paper is a mechanism in the spirit of the DOA that converges to a Walrasian equilibrium in a polynomial number of steps, thus providing a theoretical basis for the above-described empirical phenomenon. It is well-known that computation of a Walrasian equilibrium for this market corresponds to solving a maximum weight bipartite matching problem. The uncoordinated but rational responses of agents thus solve in a distributed fashion a maximum weight bipartite matching problem that is encoded by their private valuations. We show, furthermore, that every Walrasian equilibrium is reachable by some sequence of responses. This is in contrast to the well known auction algorithms for this problem which only allow one side to make offers and thus essentially choose an equilibrium that maximizes the surplus for the side making offers. Our results extend to the setting where not every agent pair is allowed to trade with each other.
Boolean-type Retractable State-finite Automata Without Outputs
Venue: arXiv cs.FL 2015
Year: 2015

An automaton $\bf A$ is called a retractable automaton if, for every subautomaton $\bf B$ of $\bf A$, there is at least one homomorphism of $\bf A$ onto $\bf B$ which leaves the elements of $B$ fixed (such homomorphism is called a retract homomorphism of $\bf A$ onto $\bf B$). We say that a retractable automaton ${\bf A}$=(A,X,$δ$) is Boolean-type if there exists a family $\{λ_B \mid \textrm{ B is a subautomaton of A } \}$ of retract homomorphisms $λ_B$ of $\bf A$ such that, for arbitrary subautomata ${\bf B}_1$ and ${\bf B}_2$ of $\bf A$, the condition $B_1\subseteq B_2$ implies $Kerλ_{B_2}\subseteq Kerλ_{B_1}$. In this paper we describe the Boolean-type retractable state-finite automata without outputs.
Integration of physical equipment and simulators for on-campus and online delivery of practical networking labs
Venue: arXiv cs.NI 2015
Year: 2015

This paper presents the design and development of a networking laboratory that integrates physical networking equipment with the open source GNS3 network simulators for delivery of practical networking classes simultaneously to both on-campus and online students. This transformation work has resulted in significant increase in laboratory capacity, reducing repeating classes. The integrated platform offers students the real world experience of using real equipment, and the convenience of easy setup and reconfiguration by using simulators. A practical exercise in setting up an OSPF/BGP network is presented as an example to illustrate the experimental design before and after the integration of GNS3 simulators. In summary, we report our experiences with the integrated platform, from infrastructure, network design to experiment design; and the learning and teaching experiences of using GNS3 in classes.
A Complex Network Approach for Collaborative Recommendation
Venue: arXiv cs.IR 2015
Year: 2015

Collaborative filtering (CF) is the most widely used and successful approach for personalized service recommendations. Among the collaborative recommendation approaches, neighborhood based approaches enjoy a huge amount of popularity, due to their simplicity, justifiability, efficiency and stability. Neighborhood based collaborative filtering approach finds K nearest neighbors to an active user or K most similar rated items to the target item for recommendation. Traditional similarity measures use ratings of co-rated items to find similarity between a pair of users. Therefore, traditional similarity measures cannot compute effective neighbors in sparse dataset. In this paper, we propose a two-phase approach, which generates user-user and item-item networks using traditional similarity measures in the first phase. In the second phase, two hybrid approaches HB1, HB2, which utilize structural similarity of both the network for finding K nearest neighbors and K most similar items to a target items are introduced. To show effectiveness of the measures, we compared performances of neighborhood based CFs using state-of-the-art similarity measures with our proposed structural similarity measures based CFs. Recommendation results on a set of real data show that proposed measures based CFs outperform existing measures based CFs in various evaluation metrics.
Project Maelstrom: Forensic Analysis of the BitTorrent-Powered Browser
Venue: arXiv cs.CR 2015
Year: 2015

In April 2015, BitTorrent Inc. released their distributed peer-to-peer powered browser, Project Maelstrom, into public beta. The browser facilitates a new alternative website distribution paradigm to the traditional HTTP-based, client-server model. This decentralised web is powered by each of the visitors accessing each Maelstrom hosted website. Each user shares their copy of the website's source code and multimedia content with new visitors. As a result, a Maelstrom hosted website cannot be taken offline by law enforcement or any other parties. Due to this open distribution model, a number of interesting censorship, security and privacy considerations are raised. This paper explores the application, its protocol, sharing Maelstrom content and its new visitor powered "web-hosting" paradigm.
Distributed Parameter Map-Reduce
Venue: arXiv cs.DC 2015
Year: 2015

This paper describes how to convert a machine learning problem into a series of map-reduce tasks. We study logistic regression algorithm. In logistic regression algorithm, it is assumed that samples are independent and each sample is assigned a probability. Parameters are obtained by maxmizing the product of all sample probabilities. Rapid expansion of training samples brings challenges to machine learning method. Training samples are so many that they can be only stored in distributed file system and driven by map-reduce style programs. The main step of logistic regression is inference. According to map-reduce spirit, each sample makes inference through a separate map procedure. But the premise of inference is that the map procedure holds parameters for all features in the sample. In this paper, we propose Distributed Parameter Map-Reduce, in which not only samples, but also parameters are distributed in nodes of distributed filesystem. Through a series of map-reduce tasks, we assign each sample parameters for its features, make inference for the sample and update paramters of the model. The above processes are excuted looply until convergence. We test the proposed algorithm in actual hadoop production environment. Experiments show that the acceleration of the algorithm is in linear relationship with the number of cluster nodes.
Approximate Fisher Kernels of non-iid Image Models for Image Categorization
Venue: arXiv cs.CV 2015
Year: 2015

The bag-of-words (BoW) model treats images as sets of local descriptors and represents them by visual word histograms. The Fisher vector (FV) representation extends BoW, by considering the first and second order statistics of local descriptors. In both representations local descriptors are assumed to be identically and independently distributed (iid), which is a poor assumption from a modeling perspective. It has been experimentally observed that the performance of BoW and FV representations can be improved by employing discounting transformations such as power normalization. In this paper, we introduce non-iid models by treating the model parameters as latent variables which are integrated out, rendering all local regions dependent. Using the Fisher kernel principle we encode an image by the gradient of the data log-likelihood w.r.t. the model hyper-parameters. Our models naturally generate discounting effects in the representations; suggesting that such transformations have proven successful because they closely correspond to the representations obtained for non-iid models. To enable tractable computation, we rely on variational free-energy bounds to learn the hyper-parameters and to compute approximate Fisher kernels. Our experimental evaluation results validate that our models lead to performance improvements comparable to using power normalization, as employed in state-of-the-art feature aggregation methods.
Evolving Twitter: an experimental analysis of graph properties of the social graph
Venue: arXiv cs.SI 2015
Year: 2015

Twitter is one of the most prominent Online Social Networks. It covers a significant part of the online worldwide population~20% and has impressive growth rates. The social graph of Twitter has been the subject of numerous studies since it can reveal the intrinsic properties of large and complex online communities. Despite the plethora of these studies, there is a limited cover on the properties of the social graph while they evolve over time. Moreover, due to the extreme size of this social network (millions of nodes, billions of edges), there is a small subset of possible graph properties that can be efficiently measured in a reasonable timescale. In this paper we propose a sampling framework that allows the estimation of graph properties on large social networks. We apply this framework to a subset of Twitter's social network that has 13.2 million users, 8.3 billion edges and covers the complete Twitter timeline (from April 2006 to January 2015). We derive estimation on the time evolution of 24 graph properties many of which have never been measured on large social networks. We further discuss how these estimations shed more light on the inner structure and growth dynamics of Twitter's social network.
An empirical study of Unfairness and Oscillation in ETSI DCC
Venue: arXiv cs.NI 2015
Year: 2015

-Performance of Vehicular Adhoc Networks (VANETs) in high node density situation has long been a major field of studies. Particular attention has been paid to the frequent exchange of Cooperative Awareness Messages (CAMs) on which many road safety applications rely. In the present paper, se focus on the European Telecommunications Standard Institute (ETSI) Decentralized Congestion Control (DCC) mechanism, particularly on the evaluation of its facility layers component when applied in the context of dense networks. For this purpose, a set of simulations has been conducted over several scenarios, considering rural highway and urban mobility in order to investigate unfairness and oscillation issues, and analyze the triggering factors. The experimental results show that the latest technical specification of the ETSI DCC presents a significant enhancement in terms of fairness. In contrast, the stability criterion leaves room for improvement as channel load measurement presents (i) considerable fluctuations when only the facility layer control is applied and (i.i) severe state oscillation when different DCC control methods are combined.
Liaison Linkages
Venue: arXiv cs.RO 2015
Year: 2015

The complete classification of hexapods - also known as Stewart Gough platforms - of mobility one is still open. To tackle this problem, we can associate to each hexapod of mobility one an algebraic curve, called the configuration curve. In this paper we establish an upper bound for the degree of this curve, assuming the hexapod is general enough. Moreover, we provide a construction of hexapods with curves of maximal degree, which is based on liaison, a technique used in the theory of algebraic curves.
Evolvable Autonomic Management
Venue: arXiv cs.OH 2015
Year: 2015

Autonomic management is aimed at adapting to uncertainty. Hence, it is devised as m-connected k-dominating set problem, resembled by dominator and dominate, such that dominators are resilient up to m-1 uncertainty among them and dominate are resilient up to k-1 uncertainty on their way to dominators. Therefore, an evolutionary algorithm GENESIS is proposed, which resolves uncertainty by evolving population of solutions, while considering uncertain constraints as sub-problems, started by initial populations by a greedy algorithm AVIDO. Theoretical analysis first justifies original problem as NP-hard problem. Eventually, the absence of polynomial time approximation scheme necessitates justification of original problem as multiobjective optimization problem. Furthermore, approximation to Pareto front is verified to be decomposed into scalar optimization sub-problems, which lays out the theoretical foundation for decomposition based evolutionary solution. Finally, case-study, feasibility analysis and exemplary implication are presented for evolvable autonomic management in combined cancer treatment with in-vivo sensor networks.
Beyond the MDS Bound in Distributed Cloud Storage
Venue: arXiv cs.CR 2015
Year: 2015

Distributed storage plays a crucial role in the current cloud computing framework. After the theoretical bound for distributed storage was derived by the pioneer work of the regenerating code, Reed-Solomon code based regenerating codes were developed. The RS code based minimum storage regeneration code (RS-MSR) and the minimum bandwidth regeneration code (RS-MBR) can achieve theoretical bounds on the MSR point and the MBR point respectively in code regeneration. They can also maintain the MDS property in code reconstruction. However, in the hostile network where the storage nodes can be compromised and the packets can be tampered with, the storage capacity of the network can be significantly affected. In this paper, we propose a Hermitian code based minimum storage regenerating (H-MSR) code and a minimum bandwidth regenerating (H-MBR) code. We first prove that our proposed Hermitian code based regenerating codes can achieve the theoretical bounds for MSR point and MBR point respectively. We then propose data regeneration and reconstruction algorithms for the H-MSR code and the H-MBR code in both error-free network and hostile network. Theoretical evaluation shows that our proposed schemes can detect the erroneous decodings and correct more errors in hostile network than the RS-MSR code and the RS-MBR code with the same code rate. Our analysis also demonstrates that the proposed H-MSR and H-MBR codes have lower computational complexity than the RS-MSR/RS-MBR codes in both code regeneration and code reconstruction.
Cooperation Alignment for Distributed Interference Management
Venue: arXiv cs.IT 2015
Year: 2015

We consider a cooperative Gaussian interference channel in which each receiver must decode its intended message locally, with the help of cooperation either at the receivers side or at the transmitter side. In the case of receiver cooperation, the receivers can process and share information through limited capacity backhaul links. In contrast to various previously considered distributed antenna architectures, where processing is utterly performed in a centralized fashion, the model considered in this paper aims to capture the essence of decentralized processing, allowing for a more general class of "interactive" interference management strategies. Focusing on the three-user case, we characterize the fundamental tradeoff between the achievable communication rates and the corresponding backhaul cooperation rate, in terms of degrees of freedom (DoF). Surprisingly, we show that the optimum communication-cooperation tradeoff per user remains the same when we move from two-user to three-user interference channels. In the absence of cooperation, this is due to interference alignment, which keeps the fraction of communication dimensions wasted for interference unchanged. When backhaul cooperation is available, we develop a new idea that we call cooperation alignment, which guarantees that the average (per user) backhaul load remains the same as we increase the number of users. In the case of transmitter cooperation, the transmitters can form their jointly precoded signals through an interactive protocol over the backhaul. In this case, we show that the optimal (per user) tradeoff between the achievable communication rates and the corresponding backhaul cooperation rate in the three-user case is the same as for receiver cooperation.